Image captioning is a typical vision-to-language problem, which aims to automatically generate descriptions for images [1]}. Recently, a line of studies used an extract-then-generate paradigm with a preliminary task, object detection [2]}. These studies first extracted a sequence of object-based region features from the images via a pre-trained detection network, and then used LSTM-based [3]} or Transformer-based [4]} sequence-to-sequence (seq2seq) models to generate captions. Empirically, the pre-extracted features greatly help models produce high-fidelity captions [2]}.
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